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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 251–300 of 1773 papers

TitleStatusHype
Usefulness of Emotional Prosody in Neural Machine Translation—0
From LLM to NMT: Advancing Low-Resource Machine Translation with Claude—0
F-MALLOC: Feed-forward Memory Allocation for Continual Learning in Neural Machine TranslationCode0
Unlocking Parameter-Efficient Fine-Tuning for Low-Resource Language Translation—0
Low-resource neural machine translation with morphological modelingCode0
Advancing AI with Integrity: Ethical Challenges and Solutions in Neural Machine Translation—0
A Tulu Resource for Machine TranslationCode0
The Comparison of Translationese in Machine Translation and Human Transation in terms of Translation Relations—0
Isometric Neural Machine Translation using Phoneme Count Ratio Reward-based Reinforcement Learning—0
CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation DataCode0
Pointer-Generator Networks for Low-Resource Machine Translation: Don't Copy That!Code0
To Label or Not to Label: Hybrid Active Learning for Neural Machine Translation—0
BiVert: Bidirectional Vocabulary Evaluation using Relations for Machine Translation—0
General2Specialized LLMs Translation for E-commerce—0
Human Evaluation of English--Irish Transformer-Based NMT—0
Leveraging Diverse Modeling Contexts with Collaborating Learning for Neural Machine Translation—0
DeMPT: Decoding-enhanced Multi-phase Prompt Tuning for Making LLMs Be Better Context-aware TranslatorsCode0
GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languages—0
Asynchronous and Segmented Bidirectional Encoding for NMT—0
Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel CorporaCode0
Large Language Models "Ad Referendum": How Good Are They at Machine Translation in the Legal Domain?—0
Promoting Target Data in Context-aware Neural Machine Translation—0
Neural Machine Translation for Malayalam Paraphrase Generation—0
Salute the Classic: Revisiting Challenges of Machine Translation in the Age of Large Language ModelsCode0
Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation—0
An approach for mistranslation removal from popular dataset for Indic MT Task—0
Machine Translation Models are Zero-Shot Detectors of Translation DirectionCode0
POMP: Probability-driven Meta-graph Prompter for LLMs in Low-resource Unsupervised Neural Machine Translation—0
End to end Hindi to English speech conversion using Bark, mBART and a finetuned XLSR Wav2Vec2—0
Towards Boosting Many-to-Many Multilingual Machine Translation with Large Language ModelsCode0
Convergences and Divergences between Automatic Assessment and Human Evaluation: Insights from Comparing ChatGPT-Generated Translation and Neural Machine Translation—0
Predicting Human Translation Difficulty with Neural Machine Translation—0
An Empirical study of Unsupervised Neural Machine Translation: analyzing NMT output, model's behavior and sentences' contribution—0
Distinguishing Translations by Human, NMT, and ChatGPT: A Linguistic and Statistical Approach—0
Unraveling Key Factors of Knowledge Distillation—0
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning—0
Improving Neural Machine Translation by Multi-Knowledge Integration with Prompting—0
Simul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models—0
Relevance-guided Neural Machine Translation—0
Reducing Gender Bias in Machine Translation through Counterfactual Data Generation—0
DP-NMT: Scalable Differentially-Private Machine TranslationCode0
Context-aware Neural Machine Translation for English-Japanese Business Scene DialoguesCode0
On Using Distribution-Based Compositionality Assessment to Evaluate Compositional Generalisation in Machine TranslationCode0
On-the-Fly Fusion of Large Language Models and Machine Translation—0
Don't Overlook the Grammatical Gender: Bias Evaluation for Hindi-English Machine TranslationCode0
Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation—0
There's no Data Like Better Data: Using QE Metrics for MT Data Filtering—0
Gender Inflected or Bias Inflicted: On Using Grammatical Gender Cues for Bias Evaluation in Machine TranslationCode0
Improving Machine Translation with Large Language Models: A Preliminary Study with Cooperative DecodingCode0
Replicable Benchmarking of Neural Machine Translation (NMT) on Low-Resource Local Languages in IndonesiaCode0
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